Inventory parameters for a serial supply chain with lost sales through genetic algorithm approach

Abstract

Supply chain is a network of facilities with varying conflicting objectives and decision making is a complex process. The uncertainty in demand increases complexity in inventory control mechanism. Backordering, partial backordering and lost-sales are considered in the inventory management to characterise the excess demand. In the present competitive scenario, mostly consumers have no patience to wait and show urgency to buy their goods failing which the management has to meet a huge loss of supply chain members and hence the profit. There are very few research works regarding lost-sales parameter in the area of multi-echelon inventory systems. It is felt that the proposed modified gene-wise genetic algorithm (MGGA) supply chain model which so far not applied in this process may help to determine best base stock levels and review periods with lost sales particularly at retailer end which minimised total supply chain cost.